Belief Updating in Treatment Resistant Depression

Overview

Major depressive disorder (MDD) is characterized by a cognitive triad of negative beliefs about oneself, the future and the world. For example, depressed patients hold persistently negative expectations about the future, despite contradictory evidence, and these strong negative beliefs are thought to play an important role in the maintenance of depressive symptoms and potentially in treatment resistance. Indeed, one out of three patients with major depressive disorder does not respond to conventional, monoaminergic treatments, which has led to the concept of treatment resistant depression (TRD). It is unknown how the brain encodes the strong negative beliefs that are insensitive to positive disconfirming information in TRD patients, and how these neural underpinnings of maladaptive belief updating are altered by antidepressant treatment. The principal objective of this study is to gain insight into the brain mechanisms of belief updating about the future in TRD patients before and after starting ketamine treatment. The results of this study are expected to provide a better understanding of the neurocognitive mechanisms of belief-updating in depressed patients, and how these mechanisms contribute to clinical improvement following ketamine antidepressant treatment.

Major depressive disorder is characterized by persistently negative expectations about the future, despite contradictory evidence, and these strong negative beliefs are thought to play an important role in the maintenance of depressive symptoms and potentially in treatment resistance. Importantly, some findings indicate that the mechanisms of clinical improvement involves reductions in negative biases in emotion processing, which is in line with cognitive theories of depression. However, it has never been studied if and how antidepressant treatment changes cognitive biases, which are important for mental health, such as the good news/bad news bias in belief updating. Moreover, it is also unknown how the brain of TRD patients encodes the strong negative beliefs that are insensitive to positive disconfirming information. The study's main goal is to test how the brain encodes belief updating in treatment resistant depressed patients before compared to early after starting an antidepressant treatment. The main outcome measure is an interaction between testing time (before vs. after a single antidepressant dose) and information valence (positive vs. negative belief disconfirming information) on the brain's oxygenation level dependent signal (BOLD). The secondary aims involve testing how belief updating changes on the behavioral level and links to global clinical improvement measured in the clinical care setting. To test these aim the study will compare the good news/bad new bias in belief updating before and after ketamine treatment. Tes the correlation of global clinical improvement to the emergence of the good news/bad news bias following antidepressant treatment.Compare the good news/bad new bias in belief updating between two groups of patients treated either by ketamine or by classical monoaminergic antidepressants that are all administered in the patient's natural clinical care setting. This study is monocentric. The patients receive antidepressant treatment as part of their routine medical care and are not randomly assigned to this treatment by the investigator (contrary to a clinical trial). The study will be run within a natural, measurement-based care setting. All patients will be tested two times, before and 24 hours after the first dose of an antidepressant medication. A total of 120 patients diagnosed with treatment resistant depression (TRD) will be enrolled in the proposed study. TRD is defined by non-response to at least two different antidepressant treatments. To test the main aim of this study 60 of the 120 TRD patients will be tested with functional magnetic resonance imaging (fMRI) before or 24h after a single subanaesthetic ketamine infusion. To be able to test the secondary aims and to run correlational analyses 60 of the 120 patients will be tested solely on the behavioral level before or 24h after a single monoaminergic antidepressant. Patients will be randomly assigned to one of two testing time point groups that will involve testing before or 24h after a first, single antidepressant treatment dosis. Randomization will be stratified to assure that each testing time group involves an equal number of participants. All patients will perform a cognitive belief updating tasks, which comprises 40 trials during which patients will be presented on a trial-by-trial basis with 40 different adverse lifetime events and information about their likelihood of occurrence in the general population (base rates, BR). The adverse lifetime events and their actual base rates are from previously published work that used to measure belief updating biases in healthy participants and in depressed patients. In total, 80 adverse lifetime events will be randomly allocated to two lists of 40 lifetime events and their actual base rates (one list per testing time point). Following the belief updating task participants will rate a subset of the 40 events on their positive/negative valence, familiarity, vividness, personal relevance (if already experienced in the past), controllability and emotional arousal using visual analogous scales (VAS, see annexe for the events rated). This measure will be used to control all analyses for potential confounds arising from inter-individual differences on them. Within the patient's usual care setting the following clinical measures will be obtained for this study, and are part of the usual psychiatric evaluation: To assess treatment resistance in unipolar TRD patients, the Maudsley Staging Method will be administered during the usual patient care setting by an experienced psychiatrist at baseline prior to the first dose of antidepressant treatment. Global clinical improvement will be measured with MADRS by the same psychiatrist trained in the administration of the MADRS. Information about age, gender, level of education will be collected and used as control variables in all statistical analyses.